FIG. 1 illustrates a power versus time plot for a modulated signal according to the prior art. Plot 100 represents the instantaneous power of the signal, with power defined by the equation Power=I2+Q2. I and Q are the in-phase and quadrature components of the waveform, respectively. Unfortunately, it can be difficult to quantify the signal shown in FIG. 1 due to its inherent randomness and inconsistencies. Consequently, a statistical description of the power levels in the signal is used to extract useful information from the signal.
One such statistical description is a complementary cumulative distribution function curve. FIG. 2 depicts a complementary cumulative distribution function curve according to the prior art. Curve 200 illustrates how much time a signal spends at or above an average power level. The x-axis is scaled to dB above the average power, and the y-axis is the percent of time the signal spends at or above the power level specified by the x-axis. The percent of time the signal spends at or above the average power defines the probability for each power level above the average. For example, in curve 200, the signal power exceeds the average power by at least 6 db approximately one percent of the time.
CCDF curves are utilized in a number of applications that use, generate, or measure modulated signals. These applications include test equipment, communication systems, and electrical components. Because a CCDF curve specifies the power characteristics of a modulated signal, it can help users and designers avoid ambiguity and errors during product design, testing, and integration. The speed at which the measurements are taken and a CCDF curve computed are therefore important to users and designers, since they affect the overall testing and usage of their products.